The effective use of the DSmT for multi-class classification

International audienceThe extension of the Dezert-Smarandache theory (DSmT) for the multi-class framework has a feasible computational complexity for various applications when the number of classes is limited or reduced typically two classes. In contrast, when the number of classes is large, the DSmT generates a high computational complexity. This paper proposes to investigate the effective use of the DSmT for multi-class classification in conjunction with the Support Vector Machines using the One-Against-All (OAA) implementation, which allows offering two advantages: firstly, it allows modeling the partial ignorance by including the complementary classes in the set of focal elements during the combination process and, secondly, it allows reducing drastically the number of focal elements using a supervised model by introducing exclusive constraints when classes are naturally and mutually exclusive. To illustrate the effective use of the DSmT for multi-class classification, two SVM-OAA implementations are combined according three steps: transformation of the SVM classifier outputs into posterior probabilities using a sigmoid technique of Platt, estimation of masses directly through the proposed model and combination of masses through the Proportional Conflict Redistribution (PCR6). To prove the effective use of the proposed framework, a case study is conducted on the handwritten digit recognition. Experimental results show that it is possible to reduce efficiently both the number of focal elements and the classification error rate

Support for UNRWA's survival

The United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) provides life-saving humanitarian aid for 5·4 million Palestine refugees now entering their eighth decade of statelessness and conflict. About a third of Palestine refugees still live in 58 recognised camps. UNRWA operates 702 schools and 144 health centres, some of which are affected by the ongoing humanitarian disasters in Syria and the Gaza Strip. It has dramatically reduced the prevalence of infectious diseases, mortality, and illiteracy. Its social services include rebuilding infrastructure and homes that have been destroyed by conflict and providing cash assistance and micro-finance loans for Palestinians whose rights are curtailed and who are denied the right of return to their homeland

The effective use of the DSmT for multi-class classification

International audienceThe extension of the Dezert-Smarandache theory (DSmT) for the multi-class framework has a feasible computational complexity for various applications when the number of classes is limited or reduced typically two classes. In contrast, when the number of classes is large, the DSmT generates a high computational complexity. This paper proposes to investigate the effective use of the DSmT for multi-class classification in conjunction with the Support Vector Machines using the One-Against-All (OAA) implementation, which allows offering two advantages: firstly, it allows modeling the partial ignorance by including the complementary classes in the set of focal elements during the combination process and, secondly, it allows reducing drastically the number of focal elements using a supervised model by introducing exclusive constraints when classes are naturally and mutually exclusive. To illustrate the effective use of the DSmT for multi-class classification, two SVM-OAA implementations are combined according three steps: transformation of the SVM classifier outputs into posterior probabilities using a sigmoid technique of Platt, estimation of masses directly through the proposed model and combination of masses through the Proportional Conflict Redistribution (PCR6). To prove the effective use of the proposed framework, a case study is conducted on the handwritten digit recognition. Experimental results show that it is possible to reduce efficiently both the number of focal elements and the classification error rate

Oral Propranolol for Treatment of Pediatric Capillary Hemangiomas

Purpose: To report the long-term results of treatment of pediatric capillary hemangiomas with oral propranolol. Methods: Three infants, 3 to 4 months of age, with periocular capillary hemangiomas were treated with oral propranolol solution (Inderal, 20mg/5ml) 2-3 mg/kg per day divided in 2 doses. Propranolol was continued up to the end of the first year of life and tapered over 2-3 weeks. All infants were followed for 20 months. Lesion size and evolution were assessed during the follow-up period. Results: Significant improvement was noted in all patients in the first 2 months of therapy with slow and continuous effect throughout the follow-up period. No serious complications were observed. Conclusion: Oral propranolol can be used as a first line agent in children with capillary hemangiomas

Clinical performance of seven prescreening tools for osteoporosis in Iranian postmenopausal women

This study was designed to evaluate seven prescreening osteoporosis models in postmenopausal Iranian women. This study was performed on 8644 postmenopausal women who have been referred for bone mineral densitometry (BMD) in BMD center of Shariati hospital in Tehran between 2001 and 2011. Diagnostic properties of seven prescreening instruments were evaluated. With regard to area under curve (AUC), these models have low accuracy (AUC a parts per thousand currency sign 0.65). Considering only femoral neck or total femur area, these models had low accuracy but were more sensitive. Except for three models with sensitivities of a parts per thousand currency sign65 % in both osteoporosis and fracture threshold, other models were around 70 % sensitive. However, these models were not considered clinically useful regarding their positive predictive values (PPV) especially in BMDs a parts per thousand currency sign02.5. With regard to different measures of diagnostic property, none of these models were good screening tools for osteoporosis or fracture threshold. Although some of them are sensitive, considering other measures such as PPV indicates that they are not completely useful for clinical use. Attempts should be made for developing newer prescreening methods and calibration of the existing models with regard to the studied population